Elsevier

Brain Research

Volume 1511, 20 May 2013, Pages 21-32
Brain Research

Research Report
Optogenetic identification of striatal projection neuron subtypes during in vivo recordings

https://doi.org/10.1016/j.brainres.2012.11.018Get rights and content

Abstract

Optogenetics has revolutionized neuroscience over the past several years by allowing researchers to modulate the activity of specific cell types, both in vitro and in vivo. One promising application of optogenetics is to use channelrhodopsin-2 (ChR2) mediated spiking to identify distinct cell types in electrophysiological recordings from awake behaving animals. In this paper, we apply this approach to in vivo recordings of the two major projection cell types in the striatum: the direct- and indirect-pathway medium spiny neurons. We expressed ChR2 in the neurons of the direct or indirect pathways using a cre-dependent viral strategy and performed electrical recordings together with optical stimulation using an implanted microwire array that included an integrated optical fiber. Despite the apparent simplicity of identifying ChR2-expressing neurons as those that respond to light, we encountered multiple potential confounds when applying this approach. Here, we describe and address these confounds and provide a Matlab tool so that others can implement our analysis methods.

This article is part of a Special Issue entitled Optogenetics (7th BRES)

Introduction

Recent advances in optogenetics have provided new approaches for perturbing the brain in a temporally precise and rapidly reversible manner (Fenno et al., 2011, Tye and Deisseroth, 2012). One of the most fruitful applications of optogenetics has been the ability to activate or inhibit specific cell types and observe the resulting changes at the behavioral level. In recent years, a second application of optogenetics has gained traction, in using light-activation to identify specific neuronal cell types during in vivo recordings. Briefly, an opsin such as ChR2 can be expressed in a subset of neurons, which are subsequently identified during a recording by their response to light. This approach has been used to identify and characterize multiple cell types in awake recordings, including fast-spiking interneurons and pyramidal neurons in cortical recordings (Cardin et al., 2009, Cardin et al., 2010, Lima et al., 2009), striatal interneurons and projection neurons (Kravitz and Kreitzer, 2011, Kravitz et al., 2012, Zhao et al., 2011), dopaminergic and GABAergic neurons in the ventral tegmental area (Cohen et al., 2012), and hippocampal interneurons (Royer et al., 2012).

One thing that is clear from examining the methods of each of these studies is that optogenetic identification protocols must be optimized for the unique composition and circuitry associated with each brain structure. We have investigated this approach in the striatum, a basal ganglia nucleus containing primarily GABAergic neurons, to identify direct and indirect pathway medium spiny projection neurons (MSNs) (Kravitz and Kreitzer, 2011, Kravitz et al., 2012). While this initially appeared to be a straightforward task of identifying cells that responded to the laser stimulation, a number of potential confounds rapidly became apparent. Most importantly, we identify scenarios in which cells might not express ChR2, but nonetheless respond to the laser stimulation with an increase in firing. These include: (1) problems with spike sorting in which spikes from a ChR2-positive unit may infiltrate a recorded ChR2-negative unit; (2) rapid synaptic activation or disinhibition through the local network; (3) short-latency visual responses and (4) photoelectric responses of the electrodes themselves. Here, we provide evidence that these caveats can be addressed and this procedure can be used to reliably identify striatal projection neuron subtypes in vivo.

Section snippets

Results

We used a cre-dependent viral strategy to express ChR2 in direct-pathway (using D1-cre mice, see Section 4) or indirect-pathway (using either D2-cre or A2A-cre mice) MSNs of the striatum (Kravitz et al., 2010, Kravitz et al., 2012). For in vivo recording, we first constructed a ferrule-fiber assembly (Fig. 1A) (Sparta et al., 2012), and then attached this assembly to a commercially-produced 32-channel microwire array (Innovative Neurophysiology, Durham, NC), such that the fiber tip was

Discussion

Neuronal circuits contain a wide structural, molecular, and functional diversity of different cell types that act together in concert. One of the major challenges facing neuroscientists is to develop new approaches to discover how these different cell types operate together as a single neuronal circuit in the awake behaving animal. Unfortunately, existing techniques for distinguishing among different cell types in vivo using electrophysiological recordings are generally either limited in their

Subjects

Bacterial artificial chromosome (BAC) transgenic mouse lines that express Cre-recombinase or fluorophores under control of the Dopamine D1 receptor (D1-Cre), D2 receptor (D2-Cre) or A2A receptor (A2A-Cre) regulatory elements were obtained from GENSAT. Animals entered the study at ∼6 weeks of age, weighing ∼20–25 g. All procedures were approved by the UCSF Institutional Animal Care and Use Committee.

Viral expression of DIO-ChR2–YFP and DIO-YFP

We used double-floxed inverted (DIO) constructs to express ChR2–YFP or ChR2–mCherry (c-Fos

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      To identify the Cre-positive cells during electrophysiological recordings, we crossed each of our Cre lines to the Ai32 line, which expresses ChR2 in a Cre-dependent manner. This allowed optogenetic tagging of our targeted cell populations [20, 54, 55]. We delivered light near the recorded neurons via an optic fiber attached to the optotrode, from a 473nm (blue light) diode-pumped solid-state laser (OEM Laser Systems, 200 mW).

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    Alexxai V. Kravitz and Scott F. Owen contributed equally to this work.

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